Homoscedasticity demands that the STATISTICAL ANALYSIS WITH SPSS FOR RESEARCH 6 different samples should be having about equal variance. (d) The data must be collected at interval and/or ratio scales of measurement to accommodate arithmetic operations of addition, division, subtraction, and multiplication that they will be subjected to. Examples of parametric statistical tests include t-tests, z-tests, analysis of variance (ANOVA), analysis of covariance (ANCOVA), multivariate analysis of variance (MANOVA), product moment correlation, regression and multiple regression. Nonparametric statistics on the other hand, use data that are collected at lower levels of measurement (nominal and ordinal scales). They have lower efficiency and do not require homogeneity of variance as well as normally distributed population.
This calculated value of n came out to be 0.5057. There were also two different methods for solving for the value of K using the best fit line given in Figure 1. By finding where the first K is equal to 1 and seeing what the Q value is at this given point, K can be solved. As said above when H equals 1 the Q value is the same as the K value. The K value was calculated to be 4.7.
Having Trial #1 and #2 being only 1 decimal place different from each other was very surprising to me, and indicated high precision. This led to a low standard deviation and a low %RSD. I think consistency of observations was what led to a high precision for me. When I added reagents to the Al(NO3)3, all the trials typically had the same observations. I stopped adding things like HCl and ammonium acetate immediately after I saw a stable
Then, the averages for each test were calculated and recorded in Table 2. The results were then transferred to Graph 1, which displays the effect of change in volume on pressure and illustrates the inverse relationship between the variables. Graph 2 demonstrates 1/volume versus pressure, and should have a linear best fit line that goes through the origin. However, due to the line of best fit not going through the origin, it is indicted that there are random and systematic errors. Graph 3 demonstrates pressure times volume versus pressure and should be a horizontal line.
The third unbuffered solution is the most basic as a result of containing the strong base, NaOH. With a measure pH of 11.93, calculated pH of 12.8, and a percent error of 7.29%, the results depict experimental errors. Unlike the unbuffered solutions, the buffered solutions are all accurate, with each solution containing a percent error less than 5.0%. This may be due to the fact that solving for buffer solutions is faster, requires less crunching of numbers, and therefore less opportunities for mistakes to
According to Case and Keats (1982), only the conventional kind 1 design is applied by huge majority of quality control practitioners due to their wider availability and case of application. Hamaker (1958) is also of the same opinion. According to Peach (1947), the subsequent are some of the major types of designing plans, rooted in the OC curves, classified according to types of protection; 1. The plan is precise by requiring the OC curve to lead through or (nearly through) two fixed points. In certain cases it may be possible to impose some additional conditions.
After this a reliability, validity and factor analysis was carried out on the data. A reliability analysis was utilized to investigate if the test efficiently assessed the construct being measured. A validity analysis allowed us to investigate if there was a relationship between the subscales of our scale and the other scales participants had to answer. Finally, a factor analysis established whether one or more of the items underlie other
versus time and 1/A versus time yielded exponential curves. The linearity of the curve of In(A) versus Time had a correlation coefficient of 0.6327. Tacitly, the deviation from expectations, assuming an ideal, perfect experiment with R2 = 1, is attributed to experimental errors (Trimm
A good argument has to fulfill the Logic Condition. There are two significantly different ways for an argument to satisfy the Logic Condition, which are if the argument is valid and if the argument is strong. An argument is valid if it has the following the conditional property such as if all the premises are true, then the conclusion cannot be false. An example of valid argument: 1. All ladies are teachers.
The predicted and experimental responses are compared in order to validate the model and to calculate the prediction error. The prediction error was found to be below 7% indicating that the observed responses were very close to the predicted values. Percentage prediction error is useful in constituting the validity of generated equations and describes how close the predicted responses to that of actual values. The values of <15 are desirable to have closeness of the predicted values with the actual values
Figure 6:synthezised diagram of DMC with Sum of square algm The above synthezised diagram is sucessfully completed by using Xilinix Syntheziser. Sum of Squares (SOSs) check that can be used to detect errors,SOS check is based on the Parseval theorem that states that the SOSs of the inputs to the FFT are equal to the SOSs of the outputs of the FFT except for a scaling factor.DMC is used for multiple bit error Detection and corrections but number of redundancy bit
Practicality. This is a process of implementing a system in an agency. Therefore, if a system is 100% accurate but fails in an agency, then it is ineffective in the agency. Whereas, a system that is easy to utilize but is ineffective in decision making, then it has no value. 9).
If a state’s quotient is higher than its geometric mean, an additional seat is allocated. The Hill method gives a very small window of opportunity for the two rounding rules to act differently. As the quotas get larger, this window gets even smaller. This method is known for slightly favoring the small states, however compared to all the other methods, it is the most unbiased for relative differences. It does a better job at minimizing those relative differences and what proportion of those differences.